Mockup designed by rawpixel.com / Freepik
A self-hosted, open-source photo management service with automatic face recognition, object detection, and semantic search — powered by modern machine learning.
demo, password is demo1234 (with sample images).This is a monorepo that consolidates what was previously five separate repositories.
| Path | What it is | Previous repo |
|---|---|---|
apps/backend/ |
Django 5 API, machine-learning pipelines, background jobs | librephotos |
apps/frontend/ |
React 18 + Vite web client, i18next localization | librephotos-frontend |
apps/mobile/ |
React Native mobile client (Android) | librephotos-mobile |
apps/docs/ |
Docusaurus site published to https://docs.librephotos.com | librephotos.docs |
deploy/ |
Dockerfiles, Compose configs, proxy, Kubernetes manifests | librephotos-docker |
Commit history from all five repositories is preserved — git log --follow apps/<app>/<file> works across the move.
Step-by-step installation instructions are available in our documentation.
| Resource | Minimum | Recommended |
|---|---|---|
| RAM | 4 GB | 8 GB+ |
| Storage | 10 GB (plus your photo library) | SSD recommended |
| CPU | 2 cores | 4+ cores |
| OS | Any Docker-compatible OS | Linux |
Note: Machine learning features (face recognition, scene classification, image captioning) are memory-intensive. 8 GB+ RAM is strongly recommended for smooth operation.
After starting LibrePhotos, interactive API docs are available at:
http://localhost:3000/api/swaggerhttp://localhost:3000/api/redocSee CONTRIBUTING.md and the per-app READMEs: - Backend - Frontend - Mobile - Docs site
The Docker Compose-based dev environment lives in deploy/compose/ and is described in the development install guide.
dev tag and update it regularly. If you find a bug, open an issue.This project is licensed under the MIT License.
$ claude mcp add librephotos \
-- python -m otcore.mcp_server <graph>